Twitter as stock market predictor
Can Twitter predict the ups and downs of the stock market?
Researchers at a US university found they were able to predict the rise and fall of the Dow Jones Industrial Average with near 90 percent accuracy several days in advance by analyzing messages on Twitter.
The researchers at Indiana University-Bloomington's School of Informatics and Computing analyzed more than 9.8 million "tweets" from 2.7 million users of the micro-blogging service during 10 months in 2008.
They measured the "collective public mood" through tweets and then compared it to closing stock market values and found a correlation between the value of the Dow and public sentiment, Indiana University said in a press release.
"What we found was an accuracy of 87.6 percent in predicting the daily up and down changes in the closing values of the Dow Jones Industrial Average," said Johan Bollen, an Indiana University associate professor who carried out the study with Ph.D. candidate Huina Mao and Xiao-Jun Zeng of the University of Manchester.
Previous studies have found a link between Twitter traffic and a movie's success or failure at the box office but the Indiana University study is believed to be the first to study Twitter and Wall Street.
Indiana University said the researchers used two mood-tracking tools -- OpinionFinder and Google's Profile of Mood States (GPOMS) -- to analyze the text content of the Twitter messages.
OpinionFinder classified tweets as positive or negative measurements of public mood. GPOMS categorized the mood of tweets as calm, alert, sure, vital, kind, and happy.
The researchers then compared the public mood measurements with Dow Jones closing values.
Bollen said "the calmness index appears to be a good predictor of whether the Dow Jones Industrial Average goes up or down between two and six days later."
In an interview with the CNBC financial news channel, Bollen said "the public mood as expressed on Twitter by millions of people posting their Twitter feeds on a daily basis fluctuates over time.
"Those fluctuations, at least one of the indications we monitor -- namely mood, calm versus anxious -- is actually correlated with the Dow Jones Industrial Average's closing values," he said.
"It was surprising to us, because we thought it would actually follow the Dow Jones Industrial Average, in the sense that if it goes up, people are happy, if it goes down people are sad," Bollen said.
"But it turns out (that) the movements in the public mood actually predated from three to four days the up and down movements of the Dow Jones Industrial Average," he said.
The study is available for download at http://arxiv.org/abs/1010.3003
Researchers at a US university found they were able to predict the rise and fall of the Dow Jones Industrial Average with near 90 percent accuracy several days in advance by analyzing messages on Twitter.
The researchers at Indiana University-Bloomington's School of Informatics and Computing analyzed more than 9.8 million "tweets" from 2.7 million users of the micro-blogging service during 10 months in 2008.
They measured the "collective public mood" through tweets and then compared it to closing stock market values and found a correlation between the value of the Dow and public sentiment, Indiana University said in a press release.
"What we found was an accuracy of 87.6 percent in predicting the daily up and down changes in the closing values of the Dow Jones Industrial Average," said Johan Bollen, an Indiana University associate professor who carried out the study with Ph.D. candidate Huina Mao and Xiao-Jun Zeng of the University of Manchester.
Previous studies have found a link between Twitter traffic and a movie's success or failure at the box office but the Indiana University study is believed to be the first to study Twitter and Wall Street.
Indiana University said the researchers used two mood-tracking tools -- OpinionFinder and Google's Profile of Mood States (GPOMS) -- to analyze the text content of the Twitter messages.
OpinionFinder classified tweets as positive or negative measurements of public mood. GPOMS categorized the mood of tweets as calm, alert, sure, vital, kind, and happy.
The researchers then compared the public mood measurements with Dow Jones closing values.
Bollen said "the calmness index appears to be a good predictor of whether the Dow Jones Industrial Average goes up or down between two and six days later."
In an interview with the CNBC financial news channel, Bollen said "the public mood as expressed on Twitter by millions of people posting their Twitter feeds on a daily basis fluctuates over time.
"Those fluctuations, at least one of the indications we monitor -- namely mood, calm versus anxious -- is actually correlated with the Dow Jones Industrial Average's closing values," he said.
"It was surprising to us, because we thought it would actually follow the Dow Jones Industrial Average, in the sense that if it goes up, people are happy, if it goes down people are sad," Bollen said.
"But it turns out (that) the movements in the public mood actually predated from three to four days the up and down movements of the Dow Jones Industrial Average," he said.
The study is available for download at http://arxiv.org/abs/1010.3003
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